High Performance Finite Element Modeling I and II

Learn how to make cutting edge adaptive FEM simulations from top researchers at KTH. These courses targets engineering students who have passed the second or third year, and engineers in industry. In part II you will learn to understand the mechanism of flight.

​​High Performance Finite Element Modeling

Engineering simulations are rapidly becoming fundamental in virtually all industrial sectors, from medicine to energy, aerospace and beyond. In these courses you will learn the breakthrough general adaptive finite element methods (AFEM) and open source FEniCS software that will enable you to solve the grand challenges in science and engineering.

These courses targets engineers in industry, or engineering students at masters and doctoral level/or towards the end of a bachelor study. Learners that achieve top grades in this first course, in a series of two courses will be offered access to a supercomputer, and more advanced simulations of turbulent flow.

Part I

After completing the course you will be able to:

derive AFEM for general PDE with relevance in industry: the Navier-Stokes equations for incompressible flow, the wave equation, linear elasticity, and multi-physics combinations of these equations.

derive fundamental properties of the methods, which are key for robustness and efficiency such as: energy conservation, stability, and a priori and a posteriori error estimates.

apply general FEM-algorithms such as assembly, adaptivity and local mesh refinement and have a basic understanding of their implementation in FEniCS-HPC.

Part II

Learn how to make cutting-edge adaptive FEM supercomputing simulations of aerodynamic principles from top researchers at KTH!

Start: spring 2018.

In this second course in the series, you will carry out advanced, time-resolved parallel simulations of aerodynamics, allowing you to understand the mechanism of flight.

Methods for deriving stability estimates for the cG(1)cG(1) FEM applied to Navier-Stokes equations.

How to account for general FEM-algorithms such as assembly, adaptvity, and local mesh refinement and have a basic understanding of their implementation in FEniCS-HPC.

How to account for parallel data structures and algorithms for distributed memory architectures in a general FEM-framework and inspect their implementation in FEniCS-HPC: distributed computational mesh, ghost entities, distributed sparse linear and non-linear algebra, local mesh refinement by bisection for a distributed computational mesh, and general goal-oriented adaptive error control.

Ways to estimate the performance of different parallel algorithms.

How to use a general framework, such as FEniCS-HPC, to model and solve general PDE on a supercomputer, and specifically aerodynamics problems with DFS.